If You Make AI Scarce, Give It All to Your Best Engineers and Learn Something
If leadership makes AI inference scarce, do not divide it equally. Give it to your best engineers, aim them at the company’s most important work, and learn what the constraint exposes.
Scarce production capacity should be allocated where it can produce the strongest evidence of value, not distributed to preserve organizational symmetry.
Concentrate scarce AI capacity where outcomes can be measured.
Equal access is not neutral when capacity is constrained. It spreads investment across unrelated work, weakens attribution, and makes a poor experiment look like a broad adoption problem.
Capital allocation requires both a capable operator and a valuable objective. Funding one without the other measures neither the tool’s ceiling nor the work’s economic return.
A time-boxed concentration is an experiment, not a permanent status hierarchy. Define the roster, the accepted outcome, the baseline, and the review date before spending begins.
Increased implementation output exposes the next constraint in the value stream. Review, testing, security, or release management must change when work begins arriving faster.
Governance should protect data, quality, and production safety. It should not disguise a flat consumption allowance as economic discipline.
When resources are scarce, name the strongest bet, fund it enough to produce a decision-grade signal, and hold leadership accountable for the result.
Scarce production capacity should be allocated where it can produce the strongest evidence of value, not distributed to preserve organizational symmetry.
Concentrate scarce AI capacity where outcomes can be measured.
Equal access is not neutral when capacity is constrained. It spreads investment across unrelated work, weakens attribution, and makes a poor experiment look like a broad adoption problem.
Capital allocation requires both a capable operator and a valuable objective. Funding one without the other measures neither the tool’s ceiling nor the work’s economic return.
A time-boxed concentration is an experiment, not a permanent status hierarchy. Define the roster, the accepted outcome, the baseline, and the review date before spending begins.
Increased implementation output exposes the next constraint in the value stream. Review, testing, security, or release management must change when work begins arriving faster.
Governance should protect data, quality, and production safety. It should not disguise a flat consumption allowance as economic discipline.
When resources are scarce, name the strongest bet, fund it enough to produce a decision-grade signal, and hold leadership accountable for the result.
After 20 years in software development, Norman is both a hands-on leader and defining the new age of AI SDLC for some of the biggest brands in the world — and exploring it with the builders. He writes here about things he is hearing and seeing. All posts are his personal points of view and do not reflect any employer or any customer he has ever had contact with.
The views and opinions expressed in this article are the author’s own and do not represent the positions of any employer, client, or affiliated organization.
